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14,558
chicago_crime
bird:train.json:8601
More crimes happened in which community area in January, 2018, Woodlawn or Lincoln Square?
SELECT T1.community_area_name FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T1.community_area_no = T2.community_area_no WHERE T1.community_area_name IN ('Woodlawn', 'Lincoln Square') AND T2.date LIKE '%1/2018%' GROUP BY T1.community_area_name ORDER BY COUNT(T1.community_area_name) DESC LIMIT 1
[ "More", "crimes", "happened", "in", "which", "community", "area", "in", "January", ",", "2018", ",", "Woodlawn", "or", "Lincoln", "Square", "?" ]
[ { "id": 0, "type": "column", "value": "community_area_name" }, { "id": 3, "type": "column", "value": "community_area_no" }, { "id": 1, "type": "table", "value": "community_area" }, { "id": 5, "type": "value", "value": "Lincoln Square" }, { "id": 4, "type": "value", "value": "Woodlawn" }, { "id": 7, "type": "value", "value": "%1/2018%" }, { "id": 2, "type": "table", "value": "crime" }, { "id": 6, "type": "column", "value": "date" } ]
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[ "O", "B-TABLE", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "O" ]
14,559
shop_membership
spider:train_spider.json:5443
What are the card numbers of members from Kentucky?
SELECT card_number FROM member WHERE Hometown LIKE "%Kentucky%"
[ "What", "are", "the", "card", "numbers", "of", "members", "from", "Kentucky", "?" ]
[ { "id": 1, "type": "column", "value": "card_number" }, { "id": 3, "type": "column", "value": "%Kentucky%" }, { "id": 2, "type": "column", "value": "hometown" }, { "id": 0, "type": "table", "value": "member" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O" ]
14,560
advertising_agencies
bird:test.json:2092
Return the client ids for clients with two or more invoices?
SELECT client_id FROM Invoices GROUP BY client_id HAVING count(*) >= 2
[ "Return", "the", "client", "ids", "for", "clients", "with", "two", "or", "more", "invoices", "?" ]
[ { "id": 1, "type": "column", "value": "client_id" }, { "id": 0, "type": "table", "value": "invoices" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,561
cs_semester
bird:train.json:899
What is the name of the course with the highest satisfaction from students?
SELECT DISTINCT T2.name FROM registration AS T1 INNER JOIN course AS T2 ON T1.course_id = T2.course_id WHERE T1.sat = 5
[ "What", "is", "the", "name", "of", "the", "course", "with", "the", "highest", "satisfaction", "from", "students", "?" ]
[ { "id": 1, "type": "table", "value": "registration" }, { "id": 5, "type": "column", "value": "course_id" }, { "id": 2, "type": "table", "value": "course" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "sat" }, { "id": 4, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
14,562
book_publishing_company
bird:train.json:207
What is the publisher that has published the most expensive book?
SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id ORDER BY T1.price DESC LIMIT 1
[ "What", "is", "the", "publisher", "that", "has", "published", "the", "most", "expensive", "book", "?" ]
[ { "id": 2, "type": "table", "value": "publishers" }, { "id": 0, "type": "column", "value": "pub_name" }, { "id": 1, "type": "table", "value": "titles" }, { "id": 4, "type": "column", "value": "pub_id" }, { "id": 3, "type": "column", "value": "price" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
14,563
pilot_1
bird:test.json:1132
What are the names of pilots between the ages of 30 and 40, ordered by age ascending?
SELECT pilot_name FROM pilotskills WHERE age BETWEEN 30 AND 40 ORDER BY age
[ "What", "are", "the", "names", "of", "pilots", "between", "the", "ages", "of", "30", "and", "40", ",", "ordered", "by", "age", "ascending", "?" ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "pilot_name" }, { "id": 2, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "30" }, { "id": 4, "type": "value", "value": "40" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 16 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,564
movies_4
bird:train.json:458
Write the person ID and character name of casts between order numbers 1 and 10 in Movie No. 285.
SELECT person_id, character_name FROM movie_cast WHERE movie_id = 285 AND cast_order BETWEEN 1 AND 10
[ "Write", "the", "person", "ID", "and", "character", "name", "of", "casts", "between", "order", "numbers", "1", "and", "10", "in", "Movie", "No", ".", "285", "." ]
[ { "id": 2, "type": "column", "value": "character_name" }, { "id": 0, "type": "table", "value": "movie_cast" }, { "id": 5, "type": "column", "value": "cast_order" }, { "id": 1, "type": "column", "value": "person_id" }, { "id": 3, "type": "column", "value": "movie_id" }, { "id": 4, "type": "value", "value": "285" }, { "id": 7, "type": "value", "value": "10" }, { "id": 6, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
14,565
superstore
bird:train.json:2430
Please list any three orders that caused a loss to the company.
SELECT `Order ID` FROM central_superstore WHERE Profit < 0 LIMIT 3
[ "Please", "list", "any", "three", "orders", "that", "caused", "a", "loss", "to", "the", "company", "." ]
[ { "id": 0, "type": "table", "value": "central_superstore" }, { "id": 1, "type": "column", "value": "Order ID" }, { "id": 2, "type": "column", "value": "profit" }, { "id": 3, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,566
party_host
spider:train_spider.json:2667
What are the first year and last year of the parties whose theme is "Spring" or "Teqnology"?
SELECT First_year , Last_year FROM party WHERE Party_Theme = "Spring" OR Party_Theme = "Teqnology"
[ "What", "are", "the", "first", "year", "and", "last", "year", "of", "the", "parties", "whose", "theme", "is", "\"", "Spring", "\"", "or", "\"", "Teqnology", "\"", "?" ]
[ { "id": 3, "type": "column", "value": "party_theme" }, { "id": 1, "type": "column", "value": "first_year" }, { "id": 2, "type": "column", "value": "last_year" }, { "id": 5, "type": "column", "value": "Teqnology" }, { "id": 4, "type": "column", "value": "Spring" }, { "id": 0, "type": "table", "value": "party" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,567
video_games
bird:train.json:3389
How many games can be played on the Wii platform?
SELECT COUNT(T1.id) FROM game_platform AS T1 INNER JOIN platform AS T2 ON T1.platform_id = T2.id WHERE T2.platform_name = 'Wii'
[ "How", "many", "games", "can", "be", "played", "on", "the", "Wii", "platform", "?" ]
[ { "id": 0, "type": "table", "value": "game_platform" }, { "id": 2, "type": "column", "value": "platform_name" }, { "id": 5, "type": "column", "value": "platform_id" }, { "id": 1, "type": "table", "value": "platform" }, { "id": 3, "type": "value", "value": "Wii" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
14,568
public_review_platform
bird:train.json:3911
What is the average number of review received by each business given that the user is an elite?
SELECT CAST(COUNT(T1.user_id) AS REAL) / COUNT(DISTINCT T1.business_id) FROM Reviews AS T1 INNER JOIN Elite AS T2 ON T1.user_id = T2.user_id
[ "What", "is", "the", "average", "number", "of", "review", "received", "by", "each", "business", "given", "that", "the", "user", "is", "an", "elite", "?" ]
[ { "id": 3, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "reviews" }, { "id": 2, "type": "column", "value": "user_id" }, { "id": 1, "type": "table", "value": "elite" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,569
movies_4
bird:train.json:552
Find the difference in percentage of the movies under keywords of "woman director" and "independent film".
SELECT CAST((SUM(CASE WHEN T1.keyword_name = 'woman director' THEN 1 ELSE 0 END) - SUM(CASE WHEN T1.keyword_name = 'independent film' THEN 1 ELSE 0 END)) AS REAL) * 100 / SUM(CASE WHEN T1.keyword_name = 'independent film' THEN 1 ELSE 0 END) FROM keyword AS T1 INNER JOIN movie_keywords AS T2 ON T1.keyword_id = T2.keyword_id
[ "Find", "the", "difference", "in", "percentage", "of", "the", "movies", "under", "keywords", "of", "\"", "woman", "director", "\"", "and", "\"", "independent", "film", "\"", "." ]
[ { "id": 7, "type": "value", "value": "independent film" }, { "id": 1, "type": "table", "value": "movie_keywords" }, { "id": 8, "type": "value", "value": "woman director" }, { "id": 6, "type": "column", "value": "keyword_name" }, { "id": 2, "type": "column", "value": "keyword_id" }, { "id": 0, "type": "table", "value": "keyword" }, { "id": 3, "type": "value", "value": "100" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O" ]
14,570
ice_hockey_draft
bird:train.json:6917
Among the players with a height of over 6'2" inches, how many of them were born in Sweden?
SELECT COUNT(T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T2.height_in_inch > '6''2"' AND T1.nation = 'Sweden'
[ "Among", "the", "players", "with", "a", "height", "of", "over", "6'2", "\"", "inches", ",", "how", "many", "of", "them", "were", "born", "in", "Sweden", "?" ]
[ { "id": 5, "type": "column", "value": "height_in_inch" }, { "id": 1, "type": "table", "value": "height_info" }, { "id": 0, "type": "table", "value": "playerinfo" }, { "id": 4, "type": "column", "value": "height_id" }, { "id": 2, "type": "column", "value": "eliteid" }, { "id": 3, "type": "column", "value": "height" }, { "id": 7, "type": "column", "value": "nation" }, { "id": 8, "type": "value", "value": "Sweden" }, { "id": 6, "type": "value", "value": "6'2\"" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 8, 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 19 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,571
cre_Students_Information_Systems
bird:test.json:478
What are the starting time and ending time of each detention record?
SELECT datetime_detention_start , datetime_detention_end FROM Detention
[ "What", "are", "the", "starting", "time", "and", "ending", "time", "of", "each", "detention", "record", "?" ]
[ { "id": 1, "type": "column", "value": "datetime_detention_start" }, { "id": 2, "type": "column", "value": "datetime_detention_end" }, { "id": 0, "type": "table", "value": "detention" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7, 8, 9, 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-TABLE", "B-COLUMN", "O" ]
14,572
soccer_2016
bird:train.json:1925
In how many games in which the batting team was the Delhi Daredevils were no runs scored?
SELECT COUNT(T1.Runs_Scored) FROM Batsman_Scored AS T1 INNER JOIN Ball_by_Ball AS T2 ON T1.Match_Id = T2.Match_Id INNER JOIN Match AS T3 ON T2.Match_Id = T3.Match_Id INNER JOIN Team AS T4 ON T3.Team_1 = T4.Team_Id WHERE T2.Team_Batting = 1 OR T2.Team_Batting = 2 AND T4.Team_Name = 'Delhi Daredevils'
[ "In", "how", "many", "games", "in", "which", "the", "batting", "team", "was", "the", "Delhi", "Daredevils", "were", "no", "runs", "scored", "?" ]
[ { "id": 12, "type": "value", "value": "Delhi Daredevils" }, { "id": 7, "type": "table", "value": "batsman_scored" }, { "id": 5, "type": "column", "value": "team_batting" }, { "id": 8, "type": "table", "value": "ball_by_ball" }, { "id": 1, "type": "column", "value": "runs_scored" }, { "id": 11, "type": "column", "value": "team_name" }, { "id": 9, "type": "column", "value": "match_id" }, { "id": 4, "type": "column", "value": "team_id" }, { "id": 3, "type": "column", "value": "team_1" }, { "id": 2, "type": "table", "value": "match" }, { "id": 0, "type": "table", "value": "team" }, { "id": 6, "type": "value", "value": "1" }, { "id": 10, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 15, 16 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 6, 7 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [ 11, 12 ] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,573
customers_and_addresses
spider:train_spider.json:6056
What are the names of all the customers?
SELECT customer_name FROM customers
[ "What", "are", "the", "names", "of", "all", "the", "customers", "?" ]
[ { "id": 1, "type": "column", "value": "customer_name" }, { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,574
books
bird:train.json:6082
What is the current address of customer Kandy?
SELECT T3.street_number, T3.street_name, T3.city FROM customer AS T1 INNER JOIN customer_address AS T2 ON T1.customer_id = T2.customer_id INNER JOIN address AS T3 ON T3.address_id = T2.address_id INNER JOIN address_status AS T4 ON T4.status_id = T2.status_id WHERE T1.first_name = 'Kandy'
[ "What", "is", "the", "current", "address", "of", "customer", "Kandy", "?" ]
[ { "id": 9, "type": "table", "value": "customer_address" }, { "id": 3, "type": "table", "value": "address_status" }, { "id": 0, "type": "column", "value": "street_number" }, { "id": 1, "type": "column", "value": "street_name" }, { "id": 11, "type": "column", "value": "customer_id" }, { "id": 4, "type": "column", "value": "first_name" }, { "id": 10, "type": "column", "value": "address_id" }, { "id": 7, "type": "column", "value": "status_id" }, { "id": 8, "type": "table", "value": "customer" }, { "id": 6, "type": "table", "value": "address" }, { "id": 5, "type": "value", "value": "Kandy" }, { "id": 2, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [ 4 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 6 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "B-VALUE", "O" ]
14,575
real_estate_rentals
bird:test.json:1452
What is the total max price of the properties owned by single mothers or students?
SELECT sum(T1.price_max) FROM Properties AS T1 JOIN Users AS T2 ON T1.owner_user_id = T2.user_id WHERE T2.user_category_code = 'Single Mother' OR T2.user_category_code = 'Student';
[ "What", "is", "the", "total", "max", "price", "of", "the", "properties", "owned", "by", "single", "mothers", "or", "students", "?" ]
[ { "id": 5, "type": "column", "value": "user_category_code" }, { "id": 3, "type": "column", "value": "owner_user_id" }, { "id": 6, "type": "value", "value": "Single Mother" }, { "id": 0, "type": "table", "value": "properties" }, { "id": 2, "type": "column", "value": "price_max" }, { "id": 4, "type": "column", "value": "user_id" }, { "id": 7, "type": "value", "value": "Student" }, { "id": 1, "type": "table", "value": "users" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 11, 12 ] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O" ]
14,576
region_building
bird:test.json:317
List the names of buildings in ascending order of number of stories.
SELECT Name FROM building ORDER BY Number_of_Stories ASC
[ "List", "the", "names", "of", "buildings", "in", "ascending", "order", "of", "number", "of", "stories", "." ]
[ { "id": 2, "type": "column", "value": "number_of_stories" }, { "id": 0, "type": "table", "value": "building" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9, 10, 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
14,578
movie_platform
bird:train.json:105
Please list the names of the movies that have been rated the most times in 2020.
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.rating_timestamp_utc LIKE '2020%' GROUP BY T2.movie_title ORDER BY COUNT(T2.movie_title) DESC LIMIT 1
[ "Please", "list", "the", "names", "of", "the", "movies", "that", "have", "been", "rated", "the", "most", "times", "in", "2020", "." ]
[ { "id": 3, "type": "column", "value": "rating_timestamp_utc" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 5, "type": "column", "value": "movie_id" }, { "id": 1, "type": "table", "value": "ratings" }, { "id": 2, "type": "table", "value": "movies" }, { "id": 4, "type": "value", "value": "2020%" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,579
shakespeare
bird:train.json:3041
Please list all of the paragraphs that have the character name Aedile.
SELECT T2.ParagraphNum FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T1.CharName = 'Aedile'
[ "Please", "list", "all", "of", "the", "paragraphs", "that", "have", "the", "character", "name", "Aedile", "." ]
[ { "id": 0, "type": "column", "value": "paragraphnum" }, { "id": 6, "type": "column", "value": "character_id" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 2, "type": "table", "value": "paragraphs" }, { "id": 3, "type": "column", "value": "charname" }, { "id": 4, "type": "value", "value": "Aedile" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
14,580
shop_membership
spider:train_spider.json:5407
What are the different cities that have more than 100 memberships?
SELECT DISTINCT city FROM branch WHERE membership_amount >= 100
[ "What", "are", "the", "different", "cities", "that", "have", "more", "than", "100", "memberships", "?" ]
[ { "id": 2, "type": "column", "value": "membership_amount" }, { "id": 0, "type": "table", "value": "branch" }, { "id": 1, "type": "column", "value": "city" }, { "id": 3, "type": "value", "value": "100" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,581
formula_1
bird:dev.json:933
What was Lewis Hamilton's final rank in the 2008 Chinese Grand Prix?
SELECT T2.positionOrder FROM races AS T1 INNER JOIN results AS T2 ON T2.raceId = T1.raceId INNER JOIN drivers AS T3 ON T3.driverId = T2.driverId WHERE T3.forename = 'Lewis' AND T3.surname = 'Hamilton' AND T1.name = 'Chinese Grand Prix' AND T1.year = 2008
[ "What", "was", "Lewis", "Hamilton", "'s", "final", "rank", "in", "the", "2008", "Chinese", "Grand", "Prix", "?" ]
[ { "id": 10, "type": "value", "value": "Chinese Grand Prix" }, { "id": 0, "type": "column", "value": "positionorder" }, { "id": 4, "type": "column", "value": "driverid" }, { "id": 5, "type": "column", "value": "forename" }, { "id": 8, "type": "value", "value": "Hamilton" }, { "id": 1, "type": "table", "value": "drivers" }, { "id": 3, "type": "table", "value": "results" }, { "id": 7, "type": "column", "value": "surname" }, { "id": 13, "type": "column", "value": "raceid" }, { "id": 2, "type": "table", "value": "races" }, { "id": 6, "type": "value", "value": "Lewis" }, { "id": 9, "type": "column", "value": "name" }, { "id": 11, "type": "column", "value": "year" }, { "id": 12, "type": "value", "value": "2008" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 2 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 3 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 10, 11, 12 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [ 9 ] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "B-VALUE", "O", "O", "O", "O", "O", "B-VALUE", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,582
bbc_channels
bird:test.json:131
What is the name of the director who is in the "Dracula" program?
SELECT t2.name FROM program AS t1 JOIN director AS t2 ON t1.director_id = t2.director_id WHERE t1.title = 'Dracula'
[ "What", "is", "the", "name", "of", "the", "director", "who", "is", "in", "the", "\"", "Dracula", "\"", "program", "?" ]
[ { "id": 5, "type": "column", "value": "director_id" }, { "id": 2, "type": "table", "value": "director" }, { "id": 1, "type": "table", "value": "program" }, { "id": 4, "type": "value", "value": "Dracula" }, { "id": 3, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-TABLE", "O" ]
14,583
movie_platform
bird:train.json:89
When was the movie Cops released?
SELECT movie_release_year FROM movies WHERE movie_title = 'Cops'
[ "When", "was", "the", "movie", "Cops", "released", "?" ]
[ { "id": 1, "type": "column", "value": "movie_release_year" }, { "id": 2, "type": "column", "value": "movie_title" }, { "id": 0, "type": "table", "value": "movies" }, { "id": 3, "type": "value", "value": "Cops" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-VALUE", "B-COLUMN", "O" ]
14,584
company_office
spider:train_spider.json:4563
Show the names of the buildings that have more than one company offices.
SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id HAVING COUNT(*) > 1
[ "Show", "the", "names", "of", "the", "buildings", "that", "have", "more", "than", "one", "company", "offices", "." ]
[ { "id": 4, "type": "table", "value": "office_locations" }, { "id": 0, "type": "column", "value": "building_id" }, { "id": 6, "type": "column", "value": "company_id" }, { "id": 2, "type": "table", "value": "companies" }, { "id": 5, "type": "table", "value": "buildings" }, { "id": 1, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 11, 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
14,585
formula_1
bird:dev.json:1005
What was the longest time a driver had ever spent at a pit stop?
SELECT duration FROM pitStops ORDER BY duration DESC LIMIT 1
[ "What", "was", "the", "longest", "time", "a", "driver", "had", "ever", "spent", "at", "a", "pit", "stop", "?" ]
[ { "id": 0, "type": "table", "value": "pitstops" }, { "id": 1, "type": "column", "value": "duration" } ]
[ { "entity_id": 0, "token_idxs": [ 12, 13 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
14,587
hr_1
spider:train_spider.json:3489
Find the job ID for those jobs which average salary is above 8000.
SELECT job_id FROM employees GROUP BY job_id HAVING AVG(salary) > 8000
[ "Find", "the", "job", "ID", "for", "those", "jobs", "which", "average", "salary", "is", "above", "8000", "." ]
[ { "id": 0, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "job_id" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 2, "type": "value", "value": "8000" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
14,588
government_shift
bird:test.json:371
Find the details of the customers who have used the least-used service .
select distinct t1.customer_details from customers as t1 join customers_and_services as t2 on t1.customer_id = t2.customer_id where t2.service_id = (select service_id from services group by service_id order by count(*) asc limit 1)
[ "Find", "the", "details", "of", "the", "customers", "who", "have", "used", "the", "least", "-", "used", "service", "." ]
[ { "id": 2, "type": "table", "value": "customers_and_services" }, { "id": 0, "type": "column", "value": "customer_details" }, { "id": 4, "type": "column", "value": "customer_id" }, { "id": 3, "type": "column", "value": "service_id" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 5, "type": "table", "value": "services" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O" ]
14,589
game_injury
spider:train_spider.json:1274
How many games are held after season 2007?
SELECT count(*) FROM game WHERE season > 2007
[ "How", "many", "games", "are", "held", "after", "season", "2007", "?" ]
[ { "id": 1, "type": "column", "value": "season" }, { "id": 0, "type": "table", "value": "game" }, { "id": 2, "type": "value", "value": "2007" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
14,590
behavior_monitoring
spider:train_spider.json:3094
What is the email of the student with first name "Emma" and last name "Rohan"?
SELECT email_address FROM Students WHERE first_name = "Emma" AND last_name = "Rohan"
[ "What", "is", "the", "email", "of", "the", "student", "with", "first", "name", "\"", "Emma", "\"", "and", "last", "name", "\"", "Rohan", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "email_address" }, { "id": 2, "type": "column", "value": "first_name" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 0, "type": "table", "value": "students" }, { "id": 5, "type": "column", "value": "Rohan" }, { "id": 3, "type": "column", "value": "Emma" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 14, 15 ] }, { "entity_id": 5, "token_idxs": [ 17 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O" ]
14,591
retail_world
bird:train.json:6368
In total, how many orders were shipped via United Package?
SELECT COUNT(T1.OrderID) FROM Orders AS T1 INNER JOIN Shippers AS T2 ON T1.ShipVia = T2.ShipperID WHERE T2.CompanyName = 'United Package'
[ "In", "total", ",", "how", "many", "orders", "were", "shipped", "via", "United", "Package", "?" ]
[ { "id": 3, "type": "value", "value": "United Package" }, { "id": 2, "type": "column", "value": "companyname" }, { "id": 6, "type": "column", "value": "shipperid" }, { "id": 1, "type": "table", "value": "shippers" }, { "id": 4, "type": "column", "value": "orderid" }, { "id": 5, "type": "column", "value": "shipvia" }, { "id": 0, "type": "table", "value": "orders" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7, 8 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "I-VALUE", "O" ]
14,592
shop_membership
spider:train_spider.json:5423
For each branch id, what are the names of the branches that were registered after 2015?
SELECT T2.name , count(*) FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year > 2015 GROUP BY T2.branch_id
[ "For", "each", "branch", "i", "d", ",", "what", "are", "the", "names", "of", "the", "branches", "that", "were", "registered", "after", "2015", "?" ]
[ { "id": 2, "type": "table", "value": "membership_register_branch" }, { "id": 4, "type": "column", "value": "register_year" }, { "id": 0, "type": "column", "value": "branch_id" }, { "id": 3, "type": "table", "value": "branch" }, { "id": 1, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "2015" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [ 17 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
14,593
movie_3
bird:train.json:9127
Please list the titles of all the films under the category of "Horror" and has a rental rate of $2.99.
SELECT T1.title FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id WHERE T3.name = 'Horror' AND T1.rental_rate = 2.99
[ "Please", "list", "the", "titles", "of", "all", "the", "films", "under", "the", "category", "of", "\"", "Horror", "\"", "and", "has", "a", "rental", "rate", "of", "$", "2.99", "." ]
[ { "id": 3, "type": "table", "value": "film_category" }, { "id": 4, "type": "column", "value": "category_id" }, { "id": 7, "type": "column", "value": "rental_rate" }, { "id": 1, "type": "table", "value": "category" }, { "id": 9, "type": "column", "value": "film_id" }, { "id": 6, "type": "value", "value": "Horror" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "film" }, { "id": 5, "type": "column", "value": "name" }, { "id": 8, "type": "value", "value": "2.99" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13 ] }, { "entity_id": 7, "token_idxs": [ 18, 19 ] }, { "entity_id": 8, "token_idxs": [ 22 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
14,594
cookbook
bird:train.json:8905
Which recipes contain almond extract?
SELECT T1.title FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T3.name = 'almond extract'
[ "Which", "recipes", "contain", "almond", "extract", "?" ]
[ { "id": 3, "type": "value", "value": "almond extract" }, { "id": 6, "type": "column", "value": "ingredient_id" }, { "id": 1, "type": "table", "value": "ingredient" }, { "id": 7, "type": "column", "value": "recipe_id" }, { "id": 5, "type": "table", "value": "quantity" }, { "id": 4, "type": "table", "value": "recipe" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3, 4 ] }, { "entity_id": 4, "token_idxs": [ 1 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
14,595
regional_sales
bird:train.json:2720
What is the name of the product with the highest net profit?
SELECT T2.`Product Name` FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID ORDER BY REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '') DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "product", "with", "the", "highest", "net", "profit", "?" ]
[ { "id": 0, "type": "column", "value": "Product Name" }, { "id": 1, "type": "table", "value": "Sales Orders" }, { "id": 4, "type": "column", "value": "_productid" }, { "id": 5, "type": "column", "value": "Unit Price" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 7, "type": "column", "value": "Unit Cost" }, { "id": 2, "type": "table", "value": "products" }, { "id": 6, "type": "value", "value": "," } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 10, 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,596
device
spider:train_spider.json:5057
Return the names of shops, ordered by year of opening ascending.
SELECT Shop_Name FROM shop ORDER BY Open_Year ASC
[ "Return", "the", "names", "of", "shops", ",", "ordered", "by", "year", "of", "opening", "ascending", "." ]
[ { "id": 1, "type": "column", "value": "shop_name" }, { "id": 2, "type": "column", "value": "open_year" }, { "id": 0, "type": "table", "value": "shop" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
14,597
local_govt_mdm
spider:train_spider.json:2659
Which distinct source system code includes the substring 'en'?
SELECT DISTINCT source_system_code FROM cmi_cross_references WHERE source_system_code LIKE '%en%'
[ "Which", "distinct", "source", "system", "code", "includes", "the", "substring", "'", "en", "'", "?" ]
[ { "id": 0, "type": "table", "value": "cmi_cross_references" }, { "id": 1, "type": "column", "value": "source_system_code" }, { "id": 2, "type": "value", "value": "%en%" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,598
food_inspection
bird:train.json:8783
How many routine inspections did Tiramisu Kitchen have?
SELECT COUNT(T1.business_id) FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.type = 'Routine - Unscheduled' AND T2.name = 'Tiramisu Kitchen'
[ "How", "many", "routine", "inspections", "did", "Tiramisu", "Kitchen", "have", "?" ]
[ { "id": 4, "type": "value", "value": "Routine - Unscheduled" }, { "id": 6, "type": "value", "value": "Tiramisu Kitchen" }, { "id": 0, "type": "table", "value": "inspections" }, { "id": 2, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "businesses" }, { "id": 3, "type": "column", "value": "type" }, { "id": 5, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 2, 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5, 6 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "B-TABLE", "B-VALUE", "B-VALUE", "I-VALUE", "O", "O" ]
14,599
school_player
spider:train_spider.json:4860
How many schools are there?
SELECT count(*) FROM school
[ "How", "many", "schools", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "school" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O" ]
14,600
book_press
bird:test.json:1977
what are the average and maximum profit of a year for all presses?
SELECT avg(Year_Profits_billion) , max(Year_Profits_billion) FROM press
[ "what", "are", "the", "average", "and", "maximum", "profit", "of", "a", "year", "for", "all", "presses", "?" ]
[ { "id": 1, "type": "column", "value": "year_profits_billion" }, { "id": 0, "type": "table", "value": "press" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,601
car_racing
bird:test.json:1636
Which countries do not have any drivers?
SELECT country FROM country WHERE country_id NOT IN (SELECT country FROM driver)
[ "Which", "countries", "do", "not", "have", "any", "drivers", "?" ]
[ { "id": 2, "type": "column", "value": "country_id" }, { "id": 0, "type": "table", "value": "country" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "table", "value": "driver" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
14,602
thrombosis_prediction
bird:dev.json:1212
For patients with alkaliphophatase (ALP) within normal range, were they treated as inpatient or outpatient?
SELECT T1.Admission FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.ALP < 300
[ "For", "patients", "with", "alkaliphophatase", "(", "ALP", ")", "within", "normal", "range", ",", "were", "they", "treated", "as", "inpatient", "or", "outpatient", "?" ]
[ { "id": 2, "type": "table", "value": "laboratory" }, { "id": 0, "type": "column", "value": "admission" }, { "id": 1, "type": "table", "value": "patient" }, { "id": 3, "type": "column", "value": "alp" }, { "id": 4, "type": "value", "value": "300" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 15 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
14,603
card_games
bird:dev.json:340
Which are the cards that have incredibly powerful foils.
SELECT id FROM cards WHERE cardKingdomFoilId IS NOT NULL AND cardKingdomId IS NOT NULL
[ "Which", "are", "the", "cards", "that", "have", "incredibly", "powerful", "foils", "." ]
[ { "id": 2, "type": "column", "value": "cardkingdomfoilid" }, { "id": 3, "type": "column", "value": "cardkingdomid" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
14,604
movie_1
spider:train_spider.json:2437
What are the titles of all movies that James Cameron directed after 2000?
SELECT title FROM Movie WHERE director = 'James Cameron' AND YEAR > 2000
[ "What", "are", "the", "titles", "of", "all", "movies", "that", "James", "Cameron", "directed", "after", "2000", "?" ]
[ { "id": 3, "type": "value", "value": "James Cameron" }, { "id": 2, "type": "column", "value": "director" }, { "id": 0, "type": "table", "value": "movie" }, { "id": 1, "type": "column", "value": "title" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "2000" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
14,606
book_publishing_company
bird:train.json:213
Which one is the cheapest business book?
SELECT title FROM titles WHERE type = 'business' ORDER BY price LIMIT 1
[ "Which", "one", "is", "the", "cheapest", "business", "book", "?" ]
[ { "id": 3, "type": "value", "value": "business" }, { "id": 0, "type": "table", "value": "titles" }, { "id": 1, "type": "column", "value": "title" }, { "id": 4, "type": "column", "value": "price" }, { "id": 2, "type": "column", "value": "type" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,607
music_4
spider:train_spider.json:6200
How many music festivals have had each kind of result, ordered descending by count?
SELECT RESULT , COUNT(*) FROM music_festival GROUP BY RESULT ORDER BY COUNT(*) DESC
[ "How", "many", "music", "festivals", "have", "had", "each", "kind", "of", "result", ",", "ordered", "descending", "by", "count", "?" ]
[ { "id": 0, "type": "table", "value": "music_festival" }, { "id": 1, "type": "column", "value": "result" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
14,609
cookbook
bird:train.json:8920
List the names of alcohol free recipes.
SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T2.alcohol = 0
[ "List", "the", "names", "of", "alcohol", "free", "recipes", "." ]
[ { "id": 2, "type": "table", "value": "nutrition" }, { "id": 5, "type": "column", "value": "recipe_id" }, { "id": 3, "type": "column", "value": "alcohol" }, { "id": 1, "type": "table", "value": "recipe" }, { "id": 0, "type": "column", "value": "title" }, { "id": 4, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
14,610
food_inspection_2
bird:train.json:6154
How much is the total fine given to Ron of Japan Inc in its inspection done on February 2014?
SELECT SUM(T3.fine) FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id WHERE strftime('%Y-%m', T2.inspection_date) = '2014-02' AND T1.dba_name = 'RON OF JAPAN INC'
[ "How", "much", "is", "the", "total", "fine", "given", "to", "Ron", "of", "Japan", "Inc", "in", "its", "inspection", "done", "on", "February", "2014", "?" ]
[ { "id": 7, "type": "value", "value": "RON OF JAPAN INC" }, { "id": 10, "type": "column", "value": "inspection_date" }, { "id": 2, "type": "table", "value": "establishment" }, { "id": 4, "type": "column", "value": "inspection_id" }, { "id": 3, "type": "table", "value": "inspection" }, { "id": 8, "type": "column", "value": "license_no" }, { "id": 0, "type": "table", "value": "violation" }, { "id": 6, "type": "column", "value": "dba_name" }, { "id": 5, "type": "value", "value": "2014-02" }, { "id": 9, "type": "value", "value": "%Y-%m" }, { "id": 1, "type": "column", "value": "fine" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
14,611
mondial_geo
bird:train.json:8357
How many mountains are there in the country with the most land area?
SELECT COUNT(Mountain) FROM geo_mountain WHERE Country = ( SELECT Code FROM country ORDER BY Area DESC LIMIT 1 )
[ "How", "many", "mountains", "are", "there", "in", "the", "country", "with", "the", "most", "land", "area", "?" ]
[ { "id": 0, "type": "table", "value": "geo_mountain" }, { "id": 2, "type": "column", "value": "mountain" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "table", "value": "country" }, { "id": 4, "type": "column", "value": "code" }, { "id": 5, "type": "column", "value": "area" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 12 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,612
flight_4
spider:train_spider.json:6811
What is the maximum elevation of all airports in the country of Iceland?
SELECT max(elevation) FROM airports WHERE country = 'Iceland'
[ "What", "is", "the", "maximum", "elevation", "of", "all", "airports", "in", "the", "country", "of", "Iceland", "?" ]
[ { "id": 3, "type": "column", "value": "elevation" }, { "id": 0, "type": "table", "value": "airports" }, { "id": 1, "type": "column", "value": "country" }, { "id": 2, "type": "value", "value": "Iceland" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
14,613
simpson_episodes
bird:train.json:4167
What's the rating of the episode in which Dan Castellaneta won the Outstanding Voice-Over Performance award in 2009?
SELECT T2.rating FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T1.award = 'Outstanding Voice-Over Performance' AND SUBSTR(T1.year, 1, 4) = '2009' AND T1.person = 'Dan Castellaneta';
[ "What", "'s", "the", "rating", "of", "the", "episode", "in", "which", "Dan", "Castellaneta", "won", "the", "Outstanding", "Voice", "-", "Over", "Performance", "award", "in", "2009", "?" ]
[ { "id": 5, "type": "value", "value": "Outstanding Voice-Over Performance" }, { "id": 8, "type": "value", "value": "Dan Castellaneta" }, { "id": 3, "type": "column", "value": "episode_id" }, { "id": 2, "type": "table", "value": "episode" }, { "id": 0, "type": "column", "value": "rating" }, { "id": 7, "type": "column", "value": "person" }, { "id": 1, "type": "table", "value": "award" }, { "id": 4, "type": "column", "value": "award" }, { "id": 6, "type": "value", "value": "2009" }, { "id": 9, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "1" }, { "id": 11, "type": "value", "value": "4" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 18 ] }, { "entity_id": 5, "token_idxs": [ 13, 14, 15, 16 ] }, { "entity_id": 6, "token_idxs": [ 20 ] }, { "entity_id": 7, "token_idxs": [ 17 ] }, { "entity_id": 8, "token_idxs": [ 9, 10 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O" ]
14,615
advertising_agencies
bird:test.json:2132
Count the number of staff in each meeting by meeting id.
SELECT meeting_id , count(*) FROM Staff_in_meetings GROUP BY meeting_id
[ "Count", "the", "number", "of", "staff", "in", "each", "meeting", "by", "meeting", "i", "d." ]
[ { "id": 0, "type": "table", "value": "staff_in_meetings" }, { "id": 1, "type": "column", "value": "meeting_id" } ]
[ { "entity_id": 0, "token_idxs": [ 4, 5, 6, 7 ] }, { "entity_id": 1, "token_idxs": [ 9, 10, 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN" ]
14,616
products_gen_characteristics
spider:train_spider.json:5538
Which category does the product named "flax" belong to?
SELECT product_category_code FROM products WHERE product_name = "flax"
[ "Which", "category", "does", "the", "product", "named", "\"", "flax", "\"", "belong", "to", "?" ]
[ { "id": 1, "type": "column", "value": "product_category_code" }, { "id": 2, "type": "column", "value": "product_name" }, { "id": 0, "type": "table", "value": "products" }, { "id": 3, "type": "column", "value": "flax" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O" ]
14,618
video_game
bird:test.json:1933
List the Title and Developers of all games ordered by units sold from large to small.
SELECT Title , Developers FROM game ORDER BY Units_sold_Millions DESC
[ "List", "the", "Title", "and", "Developers", "of", "all", "games", "ordered", "by", "units", "sold", "from", "large", "to", "small", "." ]
[ { "id": 3, "type": "column", "value": "units_sold_millions" }, { "id": 2, "type": "column", "value": "developers" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "game" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 10, 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
14,619
pilot_1
bird:test.json:1112
Count the number of pilots with age greater than 40.
SELECT count(*) FROM pilotskills WHERE age > 40
[ "Count", "the", "number", "of", "pilots", "with", "age", "greater", "than", "40", "." ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "age" }, { "id": 2, "type": "value", "value": "40" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
14,620
chicago_crime
bird:train.json:8712
How many districts are there in the police district building with a zip code of 60608?
SELECT COUNT(*) AS cnt FROM District WHERE zip_code = 60608
[ "How", "many", "districts", "are", "there", "in", "the", "police", "district", "building", "with", "a", "zip", "code", "of", "60608", "?" ]
[ { "id": 0, "type": "table", "value": "district" }, { "id": 1, "type": "column", "value": "zip_code" }, { "id": 2, "type": "value", "value": "60608" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 12, 13 ] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
14,621
restaurant
bird:train.json:1763
Among all asian restaurants in N. Milpitas Blvd., Milpitas, how many of them have restaurant ID greater than 385?
SELECT COUNT(T1.id_restaurant) AS num FROM location AS T1 INNER JOIN generalinfo AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T2.city = 'milpitas' AND T2.food_type = 'asian' AND T1.street_name = 'n milpitas blvd' AND T1.id_restaurant > 385
[ "Among", "all", "asian", "restaurants", "in", "N.", "Milpitas", "Blvd", ".", ",", "Milpitas", ",", "how", "many", "of", "them", "have", "restaurant", "ID", "greater", "than", "385", "?" ]
[ { "id": 8, "type": "value", "value": "n milpitas blvd" }, { "id": 2, "type": "column", "value": "id_restaurant" }, { "id": 1, "type": "table", "value": "generalinfo" }, { "id": 7, "type": "column", "value": "street_name" }, { "id": 5, "type": "column", "value": "food_type" }, { "id": 0, "type": "table", "value": "location" }, { "id": 4, "type": "value", "value": "milpitas" }, { "id": 6, "type": "value", "value": "asian" }, { "id": 3, "type": "column", "value": "city" }, { "id": 9, "type": "value", "value": "385" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 17 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 2 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 9, "token_idxs": [ 21 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
14,622
customers_and_orders
bird:test.json:297
Show all order status and the number of orders in each status.
SELECT order_status_code , count(*) FROM Customer_orders GROUP BY order_status_code
[ "Show", "all", "order", "status", "and", "the", "number", "of", "orders", "in", "each", "status", "." ]
[ { "id": 1, "type": "column", "value": "order_status_code" }, { "id": 0, "type": "table", "value": "customer_orders" } ]
[ { "entity_id": 0, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O" ]
14,623
inn_1
spider:train_spider.json:2585
Find the number of adults for the room reserved and checked in by CONRAD SELBIG on Oct 23, 2010.
SELECT Adults FROM Reservations WHERE CheckIn = "2010-10-23" AND FirstName = "CONRAD" AND LastName = "SELBIG";
[ "Find", "the", "number", "of", "adults", "for", "the", "room", "reserved", "and", "checked", "in", "by", "CONRAD", "SELBIG", "on", "Oct", "23", ",", "2010", "." ]
[ { "id": 0, "type": "table", "value": "reservations" }, { "id": 3, "type": "column", "value": "2010-10-23" }, { "id": 4, "type": "column", "value": "firstname" }, { "id": 6, "type": "column", "value": "lastname" }, { "id": 2, "type": "column", "value": "checkin" }, { "id": 1, "type": "column", "value": "adults" }, { "id": 5, "type": "column", "value": "CONRAD" }, { "id": 7, "type": "column", "value": "SELBIG" } ]
[ { "entity_id": 0, "token_idxs": [ 8, 9 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 10, 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
14,624
store_1
spider:train_spider.json:574
What is the company where Eduardo Martins is a customer?
SELECT company FROM customers WHERE first_name = "Eduardo" AND last_name = "Martins";
[ "What", "is", "the", "company", "where", "Eduardo", "Martins", "is", "a", "customer", "?" ]
[ { "id": 2, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 1, "type": "column", "value": "company" }, { "id": 3, "type": "column", "value": "Eduardo" }, { "id": 5, "type": "column", "value": "Martins" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,626
donor
bird:train.json:3224
Among the schools whose donators are teachers, what is the percentage of schools that are in Brooklyn?
SELECT CAST(SUM(CASE WHEN T1.school_city LIKE 'Brooklyn' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.teacher_acctid) FROM projects AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T2.is_teacher_acct = 't'
[ "Among", "the", "schools", "whose", "donators", "are", "teachers", ",", "what", "is", "the", "percentage", "of", "schools", "that", "are", "in", "Brooklyn", "?" ]
[ { "id": 2, "type": "column", "value": "is_teacher_acct" }, { "id": 6, "type": "column", "value": "teacher_acctid" }, { "id": 9, "type": "column", "value": "school_city" }, { "id": 1, "type": "table", "value": "donations" }, { "id": 4, "type": "column", "value": "projectid" }, { "id": 0, "type": "table", "value": "projects" }, { "id": 10, "type": "value", "value": "Brooklyn" }, { "id": 5, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "t" }, { "id": 7, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
14,627
movies_4
bird:train.json:526
How many movies have "vi" as their language code?
SELECT COUNT(T1.movie_id) FROM movie_languages AS T1 INNER JOIN language AS T2 ON T1.language_id = T2.language_id WHERE T2.language_code = 'vi'
[ "How", "many", "movies", "have", "\"", "vi", "\"", "as", "their", "language", "code", "?" ]
[ { "id": 0, "type": "table", "value": "movie_languages" }, { "id": 2, "type": "column", "value": "language_code" }, { "id": 5, "type": "column", "value": "language_id" }, { "id": 1, "type": "table", "value": "language" }, { "id": 4, "type": "column", "value": "movie_id" }, { "id": 3, "type": "value", "value": "vi" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,628
club_1
spider:train_spider.json:4289
Tell me the location of the club "Hopkins Student Enterprises".
SELECT clublocation FROM club WHERE clubname = "Hopkins Student Enterprises"
[ "Tell", "me", "the", "location", "of", "the", "club", "\"", "Hopkins", "Student", "Enterprises", "\"", "." ]
[ { "id": 3, "type": "column", "value": "Hopkins Student Enterprises" }, { "id": 1, "type": "column", "value": "clublocation" }, { "id": 2, "type": "column", "value": "clubname" }, { "id": 0, "type": "table", "value": "club" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
14,629
climbing
spider:train_spider.json:1129
What are the names of climbers and the corresponding names of mountains that they climb?
SELECT T1.Name , T2.Name FROM climber AS T1 JOIN mountain AS T2 ON T1.Mountain_ID = T2.Mountain_ID
[ "What", "are", "the", "names", "of", "climbers", "and", "the", "corresponding", "names", "of", "mountains", "that", "they", "climb", "?" ]
[ { "id": 3, "type": "column", "value": "mountain_id" }, { "id": 2, "type": "table", "value": "mountain" }, { "id": 1, "type": "table", "value": "climber" }, { "id": 0, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O" ]
14,630
shipping
bird:train.json:5655
What is the shipment ID of the heaviest shipment that Zachery Hicks transported?
SELECT T1.ship_id FROM shipment AS T1 INNER JOIN driver AS T2 ON T1.driver_id = T2.driver_id WHERE T2.first_name = 'Zachery' AND T2.last_name = 'Hicks' ORDER BY T1.weight DESC LIMIT 1
[ "What", "is", "the", "shipment", "ID", "of", "the", "heaviest", "shipment", "that", "Zachery", "Hicks", "transported", "?" ]
[ { "id": 5, "type": "column", "value": "first_name" }, { "id": 4, "type": "column", "value": "driver_id" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 1, "type": "table", "value": "shipment" }, { "id": 0, "type": "column", "value": "ship_id" }, { "id": 6, "type": "value", "value": "Zachery" }, { "id": 2, "type": "table", "value": "driver" }, { "id": 3, "type": "column", "value": "weight" }, { "id": 8, "type": "value", "value": "Hicks" } ]
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[ "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "B-VALUE", "O", "O" ]
14,632
books
bird:train.json:6059
Among all addresses provided by customers, identify the percentage that are not in use anymore.
SELECT CAST(SUM(CASE WHEN T2.address_status = 'Inactive' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM customer_address AS T1 INNER JOIN address_status AS T2 ON T2.status_id = T1.status_id
[ "Among", "all", "addresses", "provided", "by", "customers", ",", "identify", "the", "percentage", "that", "are", "not", "in", "use", "anymore", "." ]
[ { "id": 0, "type": "table", "value": "customer_address" }, { "id": 1, "type": "table", "value": "address_status" }, { "id": 6, "type": "column", "value": "address_status" }, { "id": 2, "type": "column", "value": "status_id" }, { "id": 7, "type": "value", "value": "Inactive" }, { "id": 3, "type": "value", "value": "100" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,633
flight_company
spider:train_spider.json:6381
How many companies operates airlines in each airport?
SELECT T3.id , count(*) FROM operate_company AS T1 JOIN flight AS t2 ON T1.id = T2.company_id JOIN airport AS T3 ON T2.airport_id = T3.id GROUP BY T3.id
[ "How", "many", "companies", "operates", "airlines", "in", "each", "airport", "?" ]
[ { "id": 2, "type": "table", "value": "operate_company" }, { "id": 4, "type": "column", "value": "airport_id" }, { "id": 5, "type": "column", "value": "company_id" }, { "id": 1, "type": "table", "value": "airport" }, { "id": 3, "type": "table", "value": "flight" }, { "id": 0, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
14,634
retail_world
bird:train.json:6342
Give the number of orders that were shipped by "Federal Shipping".
SELECT COUNT(T1.OrderID) FROM Orders AS T1 INNER JOIN Shippers AS T2 ON T1.ShipVia = T2.ShipperID WHERE T2.CompanyName = 'Federal Shipping'
[ "Give", "the", "number", "of", "orders", "that", "were", "shipped", "by", "\"", "Federal", "Shipping", "\"", "." ]
[ { "id": 3, "type": "value", "value": "Federal Shipping" }, { "id": 2, "type": "column", "value": "companyname" }, { "id": 6, "type": "column", "value": "shipperid" }, { "id": 1, "type": "table", "value": "shippers" }, { "id": 4, "type": "column", "value": "orderid" }, { "id": 5, "type": "column", "value": "shipvia" }, { "id": 0, "type": "table", "value": "orders" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O", "O" ]
14,635
loan_1
spider:train_spider.json:3035
What are the total account balances for each customer from Utah or Texas?
SELECT sum(acc_bal) FROM customer WHERE state = 'Utah' OR state = 'Texas'
[ "What", "are", "the", "total", "account", "balances", "for", "each", "customer", "from", "Utah", "or", "Texas", "?" ]
[ { "id": 0, "type": "table", "value": "customer" }, { "id": 1, "type": "column", "value": "acc_bal" }, { "id": 2, "type": "column", "value": "state" }, { "id": 4, "type": "value", "value": "Texas" }, { "id": 3, "type": "value", "value": "Utah" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
14,636
scientist_1
spider:train_spider.json:6472
What is the total number of hours for all projects?
SELECT sum(hours) FROM projects
[ "What", "is", "the", "total", "number", "of", "hours", "for", "all", "projects", "?" ]
[ { "id": 0, "type": "table", "value": "projects" }, { "id": 1, "type": "column", "value": "hours" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,637
food_inspection
bird:train.json:8782
Please list the descriptions of all the high risk violations of Tiramisu Kitchen.
SELECT DISTINCT T1.description FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' AND T2.name = 'Tiramisu Kitchen'
[ "Please", "list", "the", "descriptions", "of", "all", "the", "high", "risk", "violations", "of", "Tiramisu", "Kitchen", "." ]
[ { "id": 7, "type": "value", "value": "Tiramisu Kitchen" }, { "id": 4, "type": "column", "value": "risk_category" }, { "id": 0, "type": "column", "value": "description" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "violations" }, { "id": 2, "type": "table", "value": "businesses" }, { "id": 5, "type": "value", "value": "High Risk" }, { "id": 6, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
14,638
chicago_crime
bird:train.json:8711
How many crime against property are there?
SELECT COUNT(*) AS cnt FROM FBI_Code WHERE crime_against = 'Property'
[ "How", "many", "crime", "against", "property", "are", "there", "?" ]
[ { "id": 1, "type": "column", "value": "crime_against" }, { "id": 0, "type": "table", "value": "fbi_code" }, { "id": 2, "type": "value", "value": "Property" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O", "O", "O" ]
14,639
video_games
bird:train.json:3380
List the game IDs that were released in 2017.
SELECT T.id FROM game_platform AS T WHERE T.release_year = 2017
[ "List", "the", "game", "IDs", "that", "were", "released", "in", "2017", "." ]
[ { "id": 0, "type": "table", "value": "game_platform" }, { "id": 2, "type": "column", "value": "release_year" }, { "id": 3, "type": "value", "value": "2017" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
14,640
authors
bird:train.json:3676
Mention the titile of paper writen by Joe Lograsso.
SELECT T1.Title FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T2.Name = 'Joe Lograsso'
[ "Mention", "the", "titile", "of", "paper", "writen", "by", "Joe", "Lograsso", "." ]
[ { "id": 4, "type": "value", "value": "Joe Lograsso" }, { "id": 2, "type": "table", "value": "paperauthor" }, { "id": 6, "type": "column", "value": "paperid" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value": "paper" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 7, 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O" ]
14,641
language_corpus
bird:train.json:5776
What is the occurrence of the word "nombre"?
SELECT occurrences FROM words WHERE word = 'nombre'
[ "What", "is", "the", "occurrence", "of", "the", "word", "\"", "nombre", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "occurrences" }, { "id": 3, "type": "value", "value": "nombre" }, { "id": 0, "type": "table", "value": "words" }, { "id": 2, "type": "column", "value": "word" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
14,642
district_spokesman
bird:test.json:1194
Find the number of spokesmen for each district, and the show district names as well.
SELECT t1.name , count(*) FROM district AS t1 JOIN spokesman_district AS t2 ON t1.District_ID = t2.District_ID GROUP BY t2.District_ID
[ "Find", "the", "number", "of", "spokesmen", "for", "each", "district", ",", "and", "the", "show", "district", "names", "as", "well", "." ]
[ { "id": 3, "type": "table", "value": "spokesman_district" }, { "id": 0, "type": "column", "value": "district_id" }, { "id": 2, "type": "table", "value": "district" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O" ]
14,643
retail_world
bird:train.json:6573
Find the percentage of discontinued products in Northwind's portfolio of products.
SELECT CAST(COUNT(CASE WHEN Discontinued = 1 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(ProductID) FROM Products
[ "Find", "the", "percentage", "of", "discontinued", "products", "in", "Northwind", "'s", "portfolio", "of", "products", "." ]
[ { "id": 4, "type": "column", "value": "discontinued" }, { "id": 2, "type": "column", "value": "productid" }, { "id": 0, "type": "table", "value": "products" }, { "id": 1, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,644
car_retails
bird:train.json:1607
Of the clients whose businesses are located in the city of Boston, calculate which of them has a higher average amount of payment.
SELECT T1.customerNumber FROM customers AS T1 INNER JOIN payments AS T2 ON T1.customerNumber = T2.customerNumber WHERE T1.city = 'Boston' GROUP BY T1.customerNumber ORDER BY SUM(T2.amount) / COUNT(T2.paymentDate) DESC LIMIT 1
[ "Of", "the", "clients", "whose", "businesses", "are", "located", "in", "the", "city", "of", "Boston", ",", "calculate", "which", "of", "them", "has", "a", "higher", "average", "amount", "of", "payment", "." ]
[ { "id": 0, "type": "column", "value": "customernumber" }, { "id": 6, "type": "column", "value": "paymentdate" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "payments" }, { "id": 4, "type": "value", "value": "Boston" }, { "id": 5, "type": "column", "value": "amount" }, { "id": 3, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 23 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 21 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
14,645
planet_1
bird:test.json:1919
Which employees do not have clearance in Mars? List employee's name.
SELECT Name FROM Employee EXCEPT SELECT T2.Name FROM Has_Clearance AS T1 JOIN Employee AS T2 ON T1.Employee = T2.EmployeeID JOIN Planet AS T3 ON T1.Planet = T3.PlanetID WHERE T3.Name = "Mars";
[ "Which", "employees", "do", "not", "have", "clearance", "in", "Mars", "?", "List", "employee", "'s", "name", "." ]
[ { "id": 4, "type": "table", "value": "has_clearance" }, { "id": 8, "type": "column", "value": "employeeid" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 6, "type": "column", "value": "planetid" }, { "id": 7, "type": "column", "value": "employee" }, { "id": 2, "type": "table", "value": "planet" }, { "id": 5, "type": "column", "value": "planet" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "Mars" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 10 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
14,646
advertising_agencies
bird:test.json:2144
Return the ids, sic codes, and agency ids of clients who have attended 1 meeting and had an invoice.
SELECT T1.client_id , T1.sic_code , T1.agency_id FROM clients AS T1 JOIN meetings AS T2 ON T1.client_id = T2.client_id GROUP BY T1.client_id HAVING count(*) = 1 INTERSECT SELECT T1.client_id , T1.sic_code , T1.agency_id FROM clients AS T1 JOIN invoices AS T2 ON T1.client_id = T2.client_id
[ "Return", "the", "ids", ",", "sic", "codes", ",", "and", "agency", "ids", "of", "clients", "who", "have", "attended", "1", "meeting", "and", "had", "an", "invoice", "." ]
[ { "id": 0, "type": "column", "value": "client_id" }, { "id": 2, "type": "column", "value": "agency_id" }, { "id": 1, "type": "column", "value": "sic_code" }, { "id": 4, "type": "table", "value": "meetings" }, { "id": 6, "type": "table", "value": "invoices" }, { "id": 3, "type": "table", "value": "clients" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [ 20 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
14,647
store_product
spider:train_spider.json:4921
What city is the headquarter of the store Blackville?
SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.store_name = "Blackville"
[ "What", "city", "is", "the", "headquarter", "of", "the", "store", "Blackville", "?" ]
[ { "id": 0, "type": "column", "value": "headquartered_city" }, { "id": 5, "type": "table", "value": "store_district" }, { "id": 6, "type": "column", "value": "district_id" }, { "id": 2, "type": "column", "value": "store_name" }, { "id": 3, "type": "column", "value": "Blackville" }, { "id": 1, "type": "table", "value": "district" }, { "id": 7, "type": "column", "value": "store_id" }, { "id": 4, "type": "table", "value": "store" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,648
roller_coaster
spider:train_spider.json:6213
Show the park of the roller coaster with the highest speed.
SELECT Park FROM roller_coaster ORDER BY Speed DESC LIMIT 1
[ "Show", "the", "park", "of", "the", "roller", "coaster", "with", "the", "highest", "speed", "." ]
[ { "id": 0, "type": "table", "value": "roller_coaster" }, { "id": 2, "type": "column", "value": "speed" }, { "id": 1, "type": "column", "value": "park" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
14,649
human_resources
bird:train.json:8984
Mention the full name, hired date and performance status of the employee whose location is in Utah state.
SELECT T1.firstname, T1.lastname, T1.hiredate, T1.performance FROM employee AS T1 INNER JOIN location AS T2 ON T1.locationID = T2.locationID WHERE T2.state = 'UT'
[ "Mention", "the", "full", "name", ",", "hired", "date", "and", "performance", "status", "of", "the", "employee", "whose", "location", "is", "in", "Utah", "state", "." ]
[ { "id": 3, "type": "column", "value": "performance" }, { "id": 8, "type": "column", "value": "locationid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 2, "type": "column", "value": "hiredate" }, { "id": 4, "type": "table", "value": "employee" }, { "id": 5, "type": "table", "value": "location" }, { "id": 6, "type": "column", "value": "state" }, { "id": 7, "type": "value", "value": "UT" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [ 18 ] }, { "entity_id": 7, "token_idxs": [ 17 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,650
company_office
spider:train_spider.json:4560
What is the stories of highest building?
SELECT Stories FROM buildings ORDER BY Height DESC LIMIT 1
[ "What", "is", "the", "stories", "of", "highest", "building", "?" ]
[ { "id": 0, "type": "table", "value": "buildings" }, { "id": 1, "type": "column", "value": "stories" }, { "id": 2, "type": "column", "value": "height" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-TABLE", "O" ]
14,651
soccer_2016
bird:train.json:1980
How many matches did the Sunrisers Hyderabad team win in 2013?
SELECT SUM(CASE WHEN Match_Date LIKE '2013%' THEN 1 ELSE 0 END) FROM `Match` AS T1 INNER JOIN Team AS T2 ON T1.Match_Winner = T2.Team_Id WHERE T2.Team_Name = 'Sunrisers Hyderabad'
[ "How", "many", "matches", "did", "the", "Sunrisers", "Hyderabad", "team", "win", "in", "2013", "?" ]
[ { "id": 3, "type": "value", "value": "Sunrisers Hyderabad" }, { "id": 4, "type": "column", "value": "match_winner" }, { "id": 8, "type": "column", "value": "match_date" }, { "id": 2, "type": "column", "value": "team_name" }, { "id": 5, "type": "column", "value": "team_id" }, { "id": 0, "type": "table", "value": "Match" }, { "id": 9, "type": "value", "value": "2013%" }, { "id": 1, "type": "table", "value": "team" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5, 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 10 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "O", "O", "B-VALUE", "O" ]
14,652
allergy_1
spider:train_spider.json:463
How many different advisors are listed?
SELECT count(DISTINCT advisor) FROM Student
[ "How", "many", "different", "advisors", "are", "listed", "?" ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "advisor" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
14,653
school_bus
spider:train_spider.json:6355
Show home city where at least two drivers older than 40 are from.
SELECT home_city FROM driver WHERE age > 40 GROUP BY home_city HAVING count(*) >= 2
[ "Show", "home", "city", "where", "at", "least", "two", "drivers", "older", "than", "40", "are", "from", "." ]
[ { "id": 1, "type": "column", "value": "home_city" }, { "id": 0, "type": "table", "value": "driver" }, { "id": 2, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "40" }, { "id": 4, "type": "value", "value": "2" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O", "O" ]
14,654
election_representative
spider:train_spider.json:1193
How many distinct parties are there for representatives?
SELECT count(DISTINCT Party) FROM representative
[ "How", "many", "distinct", "parties", "are", "there", "for", "representatives", "?" ]
[ { "id": 0, "type": "table", "value": "representative" }, { "id": 1, "type": "column", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
14,655
school_finance
spider:train_spider.json:1895
List the names of the schools without any endowment.
SELECT school_name FROM school WHERE school_id NOT IN (SELECT school_id FROM endowment)
[ "List", "the", "names", "of", "the", "schools", "without", "any", "endowment", "." ]
[ { "id": 1, "type": "column", "value": "school_name" }, { "id": 2, "type": "column", "value": "school_id" }, { "id": 3, "type": "table", "value": "endowment" }, { "id": 0, "type": "table", "value": "school" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
14,656
works_cycles
bird:train.json:7424
Among all the employees who don't wish to receive promotion e-mails, how many of them belong to or once belonged to the Engineering Department?
SELECT COUNT(T1.BusinessEntityID) FROM EmployeeDepartmentHistory AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN Department AS T3 ON T1.DepartmentID = T3.DepartmentID WHERE T3.Name = 'Engineering' AND T2.EmailPromotion = 0
[ "Among", "all", "the", "employees", "who", "do", "n't", "wish", "to", "receive", "promotion", "e", "-", "mails", ",", "how", "many", "of", "them", "belong", "to", "or", "once", "belonged", "to", "the", "Engineering", "Department", "?" ]
[ { "id": 2, "type": "table", "value": "employeedepartmenthistory" }, { "id": 1, "type": "column", "value": "businessentityid" }, { "id": 7, "type": "column", "value": "emailpromotion" }, { "id": 4, "type": "column", "value": "departmentid" }, { "id": 6, "type": "value", "value": "Engineering" }, { "id": 0, "type": "table", "value": "department" }, { "id": 3, "type": "table", "value": "person" }, { "id": 5, "type": "column", "value": "name" }, { "id": 8, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
14,657
shipping
bird:train.json:5626
Determine the number of shipments delivered by Andrea Simons to Huntsville in 2016.
SELECT COUNT(*) FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id INNER JOIN driver AS T3 ON T3.driver_id = T1.driver_id WHERE T3.first_name = 'Andrea' AND T3.last_name = 'Simons' AND T2.city_name = 'Huntsville' AND STRFTIME('%Y', T1.ship_date) = '2016'
[ "Determine", "the", "number", "of", "shipments", "delivered", "by", "Andrea", "Simons", "to", "Huntsville", "in", "2016", "." ]
[ { "id": 4, "type": "column", "value": "first_name" }, { "id": 9, "type": "value", "value": "Huntsville" }, { "id": 3, "type": "column", "value": "driver_id" }, { "id": 6, "type": "column", "value": "last_name" }, { "id": 8, "type": "column", "value": "city_name" }, { "id": 13, "type": "column", "value": "ship_date" }, { "id": 1, "type": "table", "value": "shipment" }, { "id": 11, "type": "column", "value": "city_id" }, { "id": 0, "type": "table", "value": "driver" }, { "id": 5, "type": "value", "value": "Andrea" }, { "id": 7, "type": "value", "value": "Simons" }, { "id": 2, "type": "table", "value": "city" }, { "id": 10, "type": "value", "value": "2016" }, { "id": 12, "type": "value", "value": "%Y" } ]
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[ "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "B-VALUE", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
14,658
restaurant
bird:train.json:1682
Indicate street and number of the Adelitas Taqueria Restaurants.
SELECT T1.street_name, T1.street_num FROM location AS T1 INNER JOIN generalinfo AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T2.label = 'adelitas taqueria'
[ "Indicate", "street", "and", "number", "of", "the", "Adelitas", "Taqueria", "Restaurants", "." ]
[ { "id": 5, "type": "value", "value": "adelitas taqueria" }, { "id": 6, "type": "column", "value": "id_restaurant" }, { "id": 0, "type": "column", "value": "street_name" }, { "id": 3, "type": "table", "value": "generalinfo" }, { "id": 1, "type": "column", "value": "street_num" }, { "id": 2, "type": "table", "value": "location" }, { "id": 4, "type": "column", "value": "label" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O" ]
14,659
cre_Drama_Workshop_Groups
spider:train_spider.json:5171
Give me the description of the service type that offers not only the photo product but also the film product.
SELECT T1.Service_Type_Description FROM Ref_Service_Types AS T1 JOIN Services AS T2 ON T1.Service_Type_Code = T2.Service_Type_Code WHERE T2.Product_Name = 'photo' INTERSECT SELECT T1.Service_Type_Description FROM Ref_Service_Types AS T1 JOIN Services AS T2 ON T1.Service_Type_Code = T2.Service_Type_Code WHERE T2.Product_Name = 'film'
[ "Give", "me", "the", "description", "of", "the", "service", "type", "that", "offers", "not", "only", "the", "photo", "product", "but", "also", "the", "film", "product", "." ]
[ { "id": 0, "type": "column", "value": "service_type_description" }, { "id": 1, "type": "table", "value": "ref_service_types" }, { "id": 6, "type": "column", "value": "service_type_code" }, { "id": 3, "type": "column", "value": "product_name" }, { "id": 2, "type": "table", "value": "services" }, { "id": 4, "type": "value", "value": "photo" }, { "id": 5, "type": "value", "value": "film" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,660
tracking_software_problems
spider:train_spider.json:5373
Find the ids of the problems reported after 1978-06-26.
SELECT problem_id FROM problems WHERE date_problem_reported > "1978-06-26"
[ "Find", "the", "ids", "of", "the", "problems", "reported", "after", "1978", "-", "06", "-", "26", "." ]
[ { "id": 2, "type": "column", "value": "date_problem_reported" }, { "id": 1, "type": "column", "value": "problem_id" }, { "id": 3, "type": "column", "value": "1978-06-26" }, { "id": 0, "type": "table", "value": "problems" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4, 6 ] }, { "entity_id": 3, "token_idxs": [ 8, 9, 10, 11, 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
14,661
retail_world
bird:train.json:6446
What is the largest quantity of "Manjimup Dried Apples" for an order?
SELECT T2.Quantity FROM Products AS T1 INNER JOIN `Order Details` AS T2 ON T2.ProductID = T1.ProductID WHERE T1.ProductName = 'Manjimup Dried Apples' ORDER BY T2.Quantity DESC LIMIT 1
[ "What", "is", "the", "largest", "quantity", "of", "\"", "Manjimup", "Dried", "Apples", "\"", "for", "an", "order", "?" ]
[ { "id": 4, "type": "value", "value": "Manjimup Dried Apples" }, { "id": 2, "type": "table", "value": "Order Details" }, { "id": 3, "type": "column", "value": "productname" }, { "id": 5, "type": "column", "value": "productid" }, { "id": 0, "type": "column", "value": "quantity" }, { "id": 1, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O" ]
14,662
computer_student
bird:train.json:988
How many basic or medium undergraduate courses are taught by a professor?
SELECT COUNT(*) FROM course AS T1 INNER JOIN taughtBy AS T2 ON T1.course_id = T2.course_id INNER JOIN person AS T3 ON T3.p_id = T2.p_id WHERE T1.courseLevel = 'Level_300' AND T3.professor = 1
[ "How", "many", "basic", "or", "medium", "undergraduate", "courses", "are", "taught", "by", "a", "professor", "?" ]
[ { "id": 4, "type": "column", "value": "courselevel" }, { "id": 5, "type": "value", "value": "Level_300" }, { "id": 6, "type": "column", "value": "professor" }, { "id": 8, "type": "column", "value": "course_id" }, { "id": 2, "type": "table", "value": "taughtby" }, { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "table", "value": "course" }, { "id": 3, "type": "column", "value": "p_id" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O" ]
14,663
film_rank
spider:train_spider.json:4121
Return the types of film market estimations in 1995.
SELECT TYPE FROM film_market_estimation WHERE YEAR = 1995
[ "Return", "the", "types", "of", "film", "market", "estimations", "in", "1995", "." ]
[ { "id": 0, "type": "table", "value": "film_market_estimation" }, { "id": 1, "type": "column", "value": "type" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "1995" } ]
[ { "entity_id": 0, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "B-VALUE", "O" ]
14,664
customers_card_transactions
spider:train_spider.json:683
Show the number of all customers without an account.
SELECT count(*) FROM Customers WHERE customer_id NOT IN (SELECT customer_id FROM Accounts)
[ "Show", "the", "number", "of", "all", "customers", "without", "an", "account", "." ]
[ { "id": 1, "type": "column", "value": "customer_id" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "accounts" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
14,665
race_track
spider:train_spider.json:760
Give the different locations of tracks.
SELECT DISTINCT LOCATION FROM track
[ "Give", "the", "different", "locations", "of", "tracks", "." ]
[ { "id": 1, "type": "column", "value": "location" }, { "id": 0, "type": "table", "value": "track" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]